For owners of small and medium businesses

This is what shopping for AI feels like.

You don't need AI.

You need the time it frees up.

Cut hours of repetitive work every week, without changing your setup.

Book your 30-minute call →

One of the founders · No pitch · A straight answer either way

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For owners of small and medium businesses

Cut hours of repetitive work every week, without changing your setup.

Book your 30-minute call →

One of the founders · No pitch · A straight answer either way

The measurement

The number we're judged on.

Before we build anything, we agree in writing how success will be measured, usually minutes per task or hours per week. Then you run the tool and we're held to the gap between the two. What follows is the shape of it, not any one client's figures.

Hours per week · one task Illustrative
6h 4h 2h 0 Baseline · agreed in writing Build live Day 0 14 30 Day 60
  1. Day 0We agree the baseline, in writing, before any money changes hands.
  2. Day 14The build goes live and you start running it.
  3. Day 60We're judged on the gap, against the number we both signed.

Case studies

Work you can check

Case studies in this market are usually anonymous, which makes the numbers in them impossible to check. Ours name the businesses, what we built for them, and how each result is measured. Then you can check. Three of the four below carry the client's real name, with permission.

Emailed POs → factory works orders Manufacturing

Ramjet Plastics

~80%PO processing time removed · measured from order timestamps in production
The problem
Ramjet Plastics is a family-run plastic injection moulding factory in Brisbane. Every customer purchase order arrived by email and was retyped by hand: into an office order, a works order for the factory floor, and eventually an invoice. Blanket orders made it worse. A single 12,000-part monthly order had to be broken down into weekly deliveries manually, and different customers ran different rolling delivery schedules.
What we built
A system that watches the order inbox, reads each PO with AI (including PDF attachments), and extracts the line items. The office administrator reviews and approves every order before anything is committed. Approved orders generate the office order and works order PDFs automatically, splitting blanket POs into one works order per delivery date. Stock is barcode-tracked in and out.
How it's measured
PO processing time is down roughly 80%, and works orders now reach the factory floor in minutes instead of waiting in an admin queue. Every order is timestamped end to end in the system, so intake time is measured from the data rather than estimated.
Status
Live and in daily production use.
Read the full case study →
Injection moulding factory floor with orders being processed
Illustration
Three scheduling systems → one Field logistics

Oz Oils

6 hrs → 30 minDaily scheduling and booking time, five days a week
The problem
Oz Oils collects used cooking oil from around 1,300 customer sites across south-east Queensland and northern New South Wales, with four trucks and two drivers. Running the schedule meant working across three separate systems, one of which was being retired. Booking and scheduling took about six hours a day. Reschedules came in by phone, and staff kept handwritten notes to spot customers who called before their drums were full. When we imported the data, we found the manual schedule had drifted from the agreed pickup frequency for roughly one customer in three.
What we built
One platform spanning what the three systems used to do, delivered as a two-week fixed-scope build: a scheduling engine that generates recurring pickups by region and day, route planning that optimises stop order starting from each truck's live GPS position, a mobile view for drivers with one-tap navigation and litre and photo capture on completion, self-serve reschedule links for customers, and reports that flag early callers automatically instead of relying on handwritten notes.
How it's measured
Before we built anything, we signed a baseline with the client: the time spent each day on scheduling and booking. That was about six hours. It now takes about thirty minutes, which is close to twenty-seven hours a week back across a five-day week. We work that way on every engagement, and if the number hasn't got there we keep building at no extra cost until it does. Agree the measurement first, then build.
Status
In production since May 2026, running daily.
Read the full case study →
Collection truck on a regional Queensland route at dawn
Illustration
Traffic fines → driver nominations Automotive

MotorBiz

<2 minTarget per nomination, was 20–40 · audit-logged, measured in the pilot
The problem
MotorBiz is a Melbourne used-car dealership. Fines and tolls arrive addressed to the dealership as the registered owner, and the business must nominate who was actually driving, within windows as short as 28 days. Identifying the driver meant cross-referencing their dealer management system, spreadsheets, WhatsApp messages and timestamped phone photos. It took four to five hours a week, and under Victorian law, repeatedly failing to nominate can cost a company more than $22,000.
What we built
An iPad kiosk next to the key safe. Staff photograph a number plate and a driver's licence, AI extracts the details, staff confirm, and every key movement is logged with a timestamp. Fines are photographed or uploaded, the details are extracted and checked by a person, and an attribution engine matches the plate and offence time against the key log. It identifies the driver, flags the vehicle as sold, or asks for manual review. It never guesses. The system then fills the official nomination form and a browser extension loads it into the government portal, where a human ticks the captcha and presses submit. The system prepares the nomination and a person signs it, which is how we wanted it: a wrong nomination is a legal problem, not a support ticket.
How it's measured
The build targets are explicit: a nomination that took 20 to 40 minutes should take under two, and the weekly fines workload should drop from four-plus hours to under 30 minutes. Every checkout, match and submission is audit-logged, so the pilot measures those numbers in production instead of asking anyone to take our word for it.
Status
Deployed and in pilot with the dealership.
Read the full case study →
Dealership key safe and iPad kiosk
Illustration
70-page agreement → understood, consented, evidenced Aged care

Support at Home onboarding

90+Automated tests passed + independent code review · live public demo
The problem
Under the new Aged Care Act, a home-care provider can't claim funding until the client's service agreement is in place, and those agreements run 50 to 70 pages. Today a staff member walks the client through it by phone, anywhere from a two-minute "sign here" to an hour spread across several calls. Verbal consent is legally valid, but if a fee dispute surfaces later, the provider often can't prove what was actually explained. In the first two months of the new Act, complaints to the regulator jumped from about 33 a day to 43.
What we built
This one started with an aged-care lawyer rather than a paying client; we built it ahead of a provider pilot. A voice agent walks the client, or their legally authorised representative (it checks who it's talking to before taking consent from anyone), through the eight clauses that matter: services and price, contributions and the fact they can rise after Services Australia's assessment, fee increases, cancellation, the client's duty to provide a safe environment for staff, privacy, complaints, and the Statement of Rights. It answers questions using only that agreement. The legal text is stored word for word and the model is barred from rewriting it. Each clause is ticked off a live checklist before the agent captures explicit verbal consent tied to a case ID, so an interrupted call resumes where it left off.
How it's measured
The build passed more than 90 automated tests and an independent code review, and every call logs which clauses were covered and confirmed. A provider pilot can measure completeness and call time directly against today's undocumented phone calls. The demo is public. You can try it yourself.
Status
Live demo; next step is a pilot with a Support at Home provider.
Read the full case study → Try the live demo → Watch the demo call →
A family reviewing a service agreement together at a kitchen tableIllustration

The path

How it works: free until there's something worth building.

01

Book a 30-minute call

Free

Thirty minutes on a video call with one of the founders, not a salesperson. Tell us about the task that eats the most time.

02

Same-day go or no-go

Free

We'll tell you straight whether it's worth building. If it is, you get a fixed price and we agree in writing how success will be measured before any money changes hands. If it isn't, we'll say that too.

03

We build it

Fixed price, agreed up front. Prototype inside 3 days, typical first build around 14 days, integrated with the tools you already run.

04

Ongoing support

We stay on after launch, with tweaks, fixes and improvements as your business and the underlying AI change.

The people

Who you're actually talking to

Every call and every engagement is run by one of the co-founders directly.

Portrait of Brett Chilton

Brett Chilton

Co-founder

Founded Skand in 2015, a B2B software company now ten years old, with offices in Melbourne and California and customers including Queensland Rail, Sydney Trains, KiwiRail and RMIT. Brett remains an owner.

For the last three years his full-time work has been building with LLMs and wiring them into real business systems, which is what lets him tell a client honestly which tools are proven and cost-effective today, and which aren't ready to bet a business on.

Portrait of Tim Sykes

Tim Sykes

Co-founder

Built his career across capital and operations: investment analyst and senior advisor at a Melbourne family office, then owner-operator of hospitality venues and an import and distribution business. He's made payroll, fixed broken margins, and renegotiated supplier deals.

In both seats he kept seeing the same pattern: owners running on spreadsheets, burning wages on work that should have been automated, and nobody ever actually building the fix for them. That's why Hypajump exists.

Builds are delivered with our engineering team in Indonesia, working directly with the founders on every engagement.

The guarantee

We keep working until the number moves.

If the tool hasn't hit the number we agreed, we keep building until it does, at no extra cost. The price was fixed before we started and it doesn't change.

Condition 1We agree the measurement before we build.
Condition 2You actually run the tool.
Condition 3You give us an hour a week while we're iterating.

What that looks like

Say purchase orders take your administrator six hours a week. We measure it together and write the number down. We agree the target, under two hours within 60 days, and a fixed price.

Day 60, it's at three hours fifteen. That's progress but it isn't the number we agreed, so there's no new invoice. We keep going through the remaining edge cases and the awkward suppliers until it's under two.

And if we ever conclude the number isn't reachable, we say so plainly and refund you in full. That has to be true, or "we keep working" is just a way of never having to admit we were wrong.

The measurement is agreed in writing before we start: minutes per task before and after, multiplied by your loaded labour rate.

Who we're not right for

We're the wrong choice if you want a chatbot on your website by Friday, if nobody in your business can spend an hour a week with us during the build, or if the task you want automated happens less than weekly, where the maths rarely works.

If your workflow isn't worth automating, we'll tell you on the call. We have told people not to hire us. It costs us a sale and buys you a reason to trust the rest of this page.

Questions

Frequently asked

How long does a build take?

You'll hear back the same day after your call with a go or no-go on prototyping. If we proceed, the prototype lands within 3 days, and a typical first build is around 14 days from there.

Our best clients stay for months, not because builds drag, but because once the first workflow disappears they find the next one.

What does it cost?

It depends on the size of the problem. Most builds land between $3,000 and $100,000, the upper end usually when an entire end-to-end process gets taken off a team's plate.

It's worth comparing that to the right thing. A hundred thousand dollars sounds like a lot next to a software subscription. It's a different number next to the annual cost of the work you're removing: a task that occupies twenty hours a week is about a thousand hours a year, every year, and it keeps costing that until someone fixes it. Multiply it by your own loaded labour rate before you decide what's expensive.

You get a fixed price after the call, and the measurement we'll be judged on is agreed at the same time.

Do we need to change our existing tools?

Almost never. We build real API connections into the tools you already run: your CRM, your inbox, your job management, your accounting. The AI works inside your operations rather than becoming another tab you copy and paste between.

What if it doesn't work for us?

The process is built to fail fast and cheap. The first call is where we'd tell you AI isn't the right tool. The 3-day prototype proves the core mechanism before you commit to a full build.

If we still get it wrong, the guarantee above is measured against numbers we agreed before we started, so "it didn't work" is a fact we can both check rather than an argument. And it doesn't end the engagement: we keep building at no extra cost until the number moves, and only if we conclude it can't be reached does the refund follow.

The next step

Book your 30-minute call.

Pick a time below. You'll talk to one of the founders. We'll ask about the repetitive task costing you the most, and you'll leave knowing whether it's worth automating and how we'd measure the fix.

  • 30 minutes, on a video call
  • One of the founders
  • No pitch, no obligation
  • A straight answer, same day